Record link: 
http://hdl.handle.net/20.500.12708/216051
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Title: 
KDN-FLB: Knowledge-Defined Networking Through Federated Learning and Blockchain
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Citation: 
Li, Y., Donta, P. K., Wang, X., Murturi, I., Huang, M., & Dustdar, S. (2025). KDN-FLB: Knowledge-Defined Networking Through Federated Learning and Blockchain. Computer, 58(5), 16–26. https://doi.org/10.1109/MC.2024.3471984
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Publisher DOI: 
10.1109/MC.2024.3471984
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Publication Type: 
Article - Original Research Article
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Language: 
English
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Authors: 
Li, Ying 
Donta, Praveen Kumar 
Wang, Xingwei 
Murturi, Ilir 
Huang, Min 
Dustdar, Schahram 
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Organisational Unit: 
E194-02 - Forschungsbereich Distributed Systems 
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Journal: 
Computer 
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ISSN: 
0018-9162
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Date (published): 
May-2025
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Number of Pages: 
11
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Publisher: 
IEEE COMPUTER SOC
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Peer reviewed: 
Yes
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Keywords: 
Knowledge-defined Networking; Blockchain; Federated Learning; Security and Privacy
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Abstract: 
This article investigates the integration of federated learning and blockchain (FLB) technologies in developing a secure and adaptable knowledge-defined networking system, KDN-LB. It highlights KDN-FLB’s potential to enhance network performance and privacy while addressing the challenges of knowledge sharing in decentralized environments.
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Project title: 
Twinning action for spreading excellence in Artificial Intelligence of Things: 101079214 (European Commission) 
Intent-based data operation in the computing continuum: 101135576 (European Commission) 
Trustworthy, Energy-Aware federated DAta Lakes along the Computing Continuum: 101070186 (European Commission) 
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Project (external): 
National Natural Science Foundation of China
National Natural Science Foundation of China
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Project ID: 
Grant 92267206
Grant 62032013
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Research Areas: 
Information Systems Engineering: 100%
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Science Branch: 
1020 - Informatik: 100%
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